On the Equivalence of Cohen's Kappa and the Hubert-Arabie Adjusted Rand Index
نویسنده
چکیده
It is shown that one can calculate the Hubert-Arabie adjusted Rand index by first forming the fourfold contingency table counting the number of pairs of objects that were placed in the same cluster in both partitions, in the same cluster in one partition but in different clusters in the other partition, and in different clusters in both, and then computing Cohen’s κ on this fourfold table.
منابع مشابه
Nurse-Physician Agreement on Triage Category: A Reliability Analysis of Emergency Severity Index
Background and Objectives: MThe Emergency Severity Index (ESI) triage is commonly used in clinical settings to determine the patients’ emergency severity. However, the reliability of this index is not sufficiently explored. The present study examines the inter-rater reliability of ESI by comparing triage ratings as performed by nurses and physicians. Methods: This prospective cross-sectional st...
متن کاملComparing hard and overlapping clusterings
Similarity measures for comparing clusterings is an important component, e.g., of evaluating clustering algorithms, for consensus clustering, and for clustering stability assessment. These measures have been studied for over 40 years in the domain of exclusive hard clusterings (exhaustive and mutually exclusive object sets). In the past years, the literature has proposed measures to handle more...
متن کاملخوشهبندی دادههای بیانژنی توسط عدم تشابه جنگل تصادفی
Background: The clustering of gene expression data plays an important role in the diagnosis and treatment of cancer. These kinds of data are typically involve in a large number of variables (genes), in comparison with number of samples (patients). Many clustering methods have been built based on the dissimilarity among observations that are calculated by a distance function. As increa...
متن کاملclues: An R Package for Nonparametric Clustering Based on Local Shrinking
This introduction to the R package clues is a (slightly) modified version of Chang et al. (2010), published in the Journal of Statistical Software. Determining the optimal number of clusters appears to be a persistent and controversial issue in cluster analysis. Most existing R packages targeting clustering require the user to specify the number of clusters in advance. However, if this subjecti...
متن کاملCommon Dissimilarity Measures are Inappropriate for Time Series Clustering
Clustering algorithms have been actively used to identify similar time series, providing a better understanding of data. However, common clustering dissimilarity measures disregard time series correlations, yielding poor results. In this paper, we introduce a dissimilarity measure based on series partial autocorrelations. Experiments compare hierarchical clustering algorithms using the common d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Classification
دوره 25 شماره
صفحات -
تاریخ انتشار 2008